Computer Science is Not About Computers… and tasting a bit of Syntactic Sugar

I finally got around to watching the first of the SICP lectures. This first third of it is a real treat for those with a mathematical bent. I summarize Sussman’s Abelson’s argument here:

Computer Science is not a science.

Computer Science is not about computers.

Computer Science is not even “real.”

Geometry is not about Surveying or Surveying instruments.

Geometry is about an using axioms and logic to provide a framework for exploring declarative knowledge– identifying and articulating what is true.

Similarly, Computer Science is really about imperative knowledge– articulating how to do things.

Computer Science deals with idealized components. There’s not all that much difference between what you can build and what you can imagine. The constraints imposed in building large software systems are not physical constraints, but rather the constraints are the limitations imposed by your own mind.

Computer Science is therefore an abstract form of engineering.

The second portion of the lecture dealt with an overview of the course. SICP is going to focus on programming techniques for controlling complexity. Sussman made something as simple as Black Box Abstraction sound really interesting: the key to that was in how he highlighted that we’re not just going to build black boxes, but that we’re also also going to build black boxes that return other black boxes… and by passing black boxes as parameters, we’ll be able to obtain another order of magnitude of abstraction in our programming style that is far beyond what non-functional programmers tend to think in. He spent less time selling us on the Conventional Interfaces section, though he did mention that this part would hit on OOP somewhat. The final portion of the course on Making New Languages sounded the most exciting– but his brief description of Metalinguistic Abstraction sounded (at this point, mind you) pointlessly geeky and pedantic. I must as of yet lack some sort of illumination, because I suspect that my mind should be blown away by the mere hint of the magic of Eval and Apply….

In the last section of the lecture he went over a bare bones introduction to Lisp. He was using Scheme– and even though I have gotten DrScheme up and running with almost no hassle, I still recoil at the thought of spending any time away from Common Lisp, Slime, and Emacs. Nevertheless, the Scheme approach is very clean and slightly more intuitive than the traditional Common Lisp way of doing things. Just for fun I wrote a macro that implements some of the functionality of Scheme’s define operator:

Note that the second case there was somewhat more tricky to implement. I tried several different ways of doing it with setf and defun before getting a version that would work identically to the first case. The key (or possibly the ‘hack’) was to define the function with the arguments from the lambda… and then splice those arguments in with ,@ after the lambda expression. I think I had this same difficulty when I was trying to understand Michael Harrison’s example from the Little Schemer a few weeks ago– Scheme and Common Lisp seem to work in subtly different manners in this case. But working through this example has helped me understand the differences a little better.

Anyways, the most shocking thing in the lecture for me was when Sussman blithely tossed out the phrase “syntactic sugar.” (He defined it as “somewhat more convenient surface forms for typing something.”) I usually associate this phrase with smarty pants blogger types that really want to sound cool. Yeah, like all you need to do to sound cool is to criticize Java a little and throw this phrase around!! Now that I’ve seen it turn up here, I guess I’ll have to get down off my high horse the next time my hackles are raised over this….